1350-P: Ehealth Technologies for Gestational Diabetes Mellitus: Summary of Features and Effectiveness: Scoping Review
Bibliographic record
Abstract
Background: There has been growing availability of ehealth technologies (ETs) for management of gestational diabetes mellitus (GDM). While ETs have the potential to improve the efficiency and quality of GDM care, the nature of information and support provided through such technologies and their benefits are unclear. This review aims to summarise data on features and outcomes for ETs specific to GDM. Methods: We conducted a systematic literature search of studies on ehealth technologies in EMBASE, OVID, SCOPUS and Web of Science in November 2019. Studies reporting data on use of ETs for management and follow up of women with GDM were included. Results: We identified 17 studies with data on over 2,000 women with GDM that described ETs for management and follow up of women GDM. The studies were categorised into telemedicine (n=4), web-based (n=4) and smartphone application (n=9). The types of studies included in the review include randomized controlled trials (n=9), cohort studies (n=3), quasi experimental study (n=3) and focus group discussions (n=2). Some features of the ETs include electronic transfer of blood glucose data, bidirectional communication with physician, web based lifestyle program and a virtual diary to log blood glucose measurements (BGM), step count and dietary intake. Studies evaluating telemedicine and web based systems showed significant reductions in the number of in person clinic visits during pregnancy (2 studies), better glycemic control (2 studies), lowered insulin use (2 studies), and weight loss after delivery (1 study). Studies that evaluated smartphone applications showed significantly higher adherence to BGM (4 studies), patient satisfaction (92% in one study) and acceptance through thematic evaluation of app (5 studies), supporting the potential of smartphone app for managing GDM. Conclusion: Ehealth technologies have the potential to improve management and outcomes for women with GDM. Disclosure B. Balaji: None. I. Halperin: Advisory Panel; Self; Tandem Diabetes Care. Speaker’s Bureau; Self; Abbott, Boehringer Ingelheim (Canada) Ltd., Dexcom, Inc., Novo Nordisk Inc., Sanofi. G. Mukerji: None. L. Lipscombe: None.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".